code: def test_product(dtype, nelem):
      np.random.seed(0)
      dtype = cudf.dtype(dtype).type
      if cudf.dtype(dtype).kind in {"u", "i"}:
          data = np.ones(nelem, dtype=dtype)
          # Set at most 30 items to [0..2) to keep the value within 2^32
          for _ in range(30):
              data[np.random.randint(low=0, high=nelem, size=1)] = (
                  np.random.uniform() * 2
              )
      else:
          data = gen_rand(dtype, nelem)
  
      sr = Series(data)
  
      got = sr.product()
      expect = pd.Series(data).product()
      significant = 4 if dtype == np.float32 else 6
      np.testing.assert_approx_equal(
          expect, got, significant=significant
      )
  
imports: from decimal import Decimal
  from itertools import product
  import numpy
  import pandas
  import pytest
  import cudf
  from cudf import Series
  from cudf.core.dtypes import Decimal32Dtype, Decimal64Dtype, Decimal128Dtype
  from cudf.testing import _utils
  from cudf.testing._utils import NUMERIC_TYPES, assert_eq, expect_warning_if, gen_rand
label_desc: Use image node_id 4 for calling a global function with example usage: test_product(dtype, nelem) without return types